This is a simple online glossary of terms that are commonly found in machine learning papers.

Frequently Asked Questions

Who is the audience for Machine Learning Glossary?

The definitions are written to be understandable for someone with half of an undergraduate degree in Computer Science. A basic knowledge of software engineering, calulus, probability, and statistics is assumed. However, anything beyond a basic knowledge should be explained and defined here.

Who maintains Machine Learning Glossary?

James Mishra is the maintainer.

What is the motivation for Machine Learning Glossary?

Machine learning papers have many complicated sounding terms, and common-sense definitions and explanations on the Internet can still be too verbose or require too much prior knowledge to understand.

Machine Learning Glossary is a fast-loading website filled with simple explanations.

How can I contribute to Machine Learning Glossary?

The source material for Machine Learning Glossary is on Github. We welcome improvements to existing terms as well as the addition of new terms.

At the top of each page, there are links to Edit this page or Report an issue. You will need a Github account to suggest edits or create issues.